Felipe Ortega, Ángel and Pardo Llorente, Leandro
(2007)
*New Family Of Estimators For The Loglinear Model Of Quasi-Independence Based On Power-Divergence Measures.*
Journal of Statistical Computation and Simulation, 77
(5).
pp. 407-420.
ISSN 0094-9655

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Official URL: http://www.tandfonline.com/doi/pdf/10.1080/10629360600890154

## Abstract

We study the minimum power-divergence estimator, introduced and studied by N. Cressie and T. R. C. Read [Multinomial goodness-of-fit tests. J. R. Stat. Soc., Ser. B 46, 440–464 (1984), in the loglinear model of quasi-independence.

A simulation study illustrates that minimum chi-squared estimator and Cressie-Read estimator are good alternatives to the classical maximum-likelihood estimator for this

problem.

The estimator obtained for = 2 is the most robust and efficient estimator among the family of the minimum power estimators.

Item Type: | Article |
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Additional Information: | loglinear model, quasi-independence, maximum likelihood, minimum powerdivergence estimator |

Uncontrolled Keywords: | Loglinear Model; Quasi-Independence; Maximum Likelihood; Minimum Power-Divergence Estimator;Minimum; Distance; Computer Science, Interdisciplinary Applications; Statistics & Probability |

Subjects: | Sciences > Mathematics > Differential equations |

ID Code: | 15086 |

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Deposited On: | 04 May 2012 11:34 |

Last Modified: | 06 Feb 2014 10:16 |

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